Hvac system and control methods for operation within a microgrid

ABSTRACT

An HVAC renewable energy management system and components to enable the efficient use of locally produced power from an onsite nanogrid and interconnected nanogrids of a cohesive direct current microgrid network. The system comprises a central controller for controlling one or more intermittent distributed energy resource (DER), source converter, distributed storage device, energy storage converter, power bus, internal load, and interface gateway to one or more external grid for bi-directional power control, sharing, and consumption. System hardware and software elements are configured for internetworking communication, management, control, demand side management, and power balance, using maximum power point tracking to shift power consumption, dynamic matching of local DER production, power quality assurance, system protection, power interconnection management, interface management, metering, revenue settlement, system optimization, and security. The system can match local power production with an individual household&#39;s power consumption to reduce intermittency and ultimately total microgrid consumption.

FIELD

The present disclosure relates to the field of heating ventilation andair conditioning (HVAC) systems; particularly, a renewable energymanagement system for HVAC applications within a cohesive microgridnetwork of nanogrids.

BACKGROUND

The US electric power grid is undergoing modernization to make the grid“smart.” A smart grid is an electrical power delivery system where powerquality, efficiency, and energy costs are optimized by pervasive use ofinformation and communication technology with the aim to controldistributed energy resources. The next-generation smart gridtechnologies include battery storage, electric vehicles, dispatchableloads, and microgrids.

A microgrid is a group of interconnected loads and distributed energyresources within clearly defined electrical boundaries that acts as asingle controllable entity with respect to the grid. A microgrid canconnect and disconnect from the grid to enable it to operate in bothgrid-connected or island mode (U.S. Department of Energy MicrogridExchange Group). It is a concept that incorporates distributed energyresources (DER), such as Photovoltaic (PV) generators and small windturbines, as well as distributed generation (DG) and distributed storage(DS). DG units are generally small generators and DS units can be forexample batteries or electric vehicles (EVs).

A nanogrid is a power distribution system for a single house or a smallbuilding, with the ability to connect or disconnect from other powerentities via a gateway. It consists of local power production from aDER, generally a PV generator, powering internal loads, with the optionof utilizing a DS energy storage and or an energy management controlsystem (EMS). EMS' s generally include a supply side management (SSM)and demand side management (DSM). An SSM focuses on controlling thenanogrid's supplies and energy storage to ensure that demand loads aremet and at an optimal battery State of Charge (SoC), while a DSMmanipulates the various internal loads to meet the characteristics ofthe power supply. DSM, power quality, imbalance/asymmetry, plug-and-playoperation of DER systems, distributed voltage/frequency profile control,and non-autonomous/autonomous operation are some of the challenges inoperating a nanogrid. However, a microgrid can be created byinterconnecting nanogrids together to create a hierarchical power systemthat enables power sharing and communications within a diverse communityof power consumers. The major components of a microgrid are ahierarchical control approach, a point of common coupling (PCC),distributed controls using local information, and a specific region thatenables DG units to be integrated in a systematic way to ensure reliableoperation of the system. In a smart grid, there are two way flows ofelectricity and information, whereby consumers and producers (e.g.,utility companies) could exchange real-time information (e.g.,electricity prices, power usages) through for example smart meters. Anetwork of communication devices provides the microgrid with thenecessary intelligence to allow customers and utility companies tocollaboratively manage power generated, delivered, and consumed throughreal-time, bidirectional communications. However, a securedcommunication is essential in order to ensure the proper stability andoperation of all the microgrid and nanogrid components.

Alternating Current (AC) systems have been dominant in power systems formore than a century, but these traditional AC systems have been affectedby recent developments such as the emergence of power electronics andthe increasing interest in renewable energy sources. The majority of thepresent residential electric appliances work with AC voltage; thus,power electronics-based systems are needed for converting the DC voltagethat is generated by renewable DERs to the AC voltage. AC microgridsrepresent the AC power supply in a distribution network. They can beeasily connected to an existing grid utility without specialrequirements such as converters and their control approaches. However,the loads being served by today's AC grid are becoming more nativelyDirect Current (DC), and DC microgrids are garneringg more focus due tobetter short circuit protection, lower losses, enhanced efficiency, noreactive power, the proliferation of modern electronic equipment, andthe availability of environmentally friendly DC sources (solar and fuelcells). Many appliances in residential homes are operated using DCpower, such as TVs, computers, DC water heaters and lighting. A heating,ventilation, and air conditioning (HVAC) system consumes a significantportion of residential power. The U.S. Energy Information Administration(EIA) estimates that 18% of annual household electricity use is for airconditioning. Three-quarters of all air-conditioned homes use centralequipment (EIA, 2017) currently operating under AC power. Motor-drivencomponents (e.g., fans) used in HVAC and refrigeration are the highestenergy consumers in both the residential and commercial sectors. In theresidential sector, HVAC applications account for 63% of motor-drivenenergy use, and refrigeration accounts for 28%. Direct-DC power systemscan provide energy and cost savings in the residential built environment(including net zero energy homes), in which electricity is generated,distributed, and consumed in DC. Advanced brushless DC (permanentmagnet) motors can save 5-15% of the energy used by traditional ACinduction motors and up to 30-50% in variable-speed drives (VSD)applications for pumping, ventilation, refrigeration, and space cooling(K. Garbesi, V. Vossos, H. Shen, Catalog of DC Appliances and PowerSystems, Lawrence Berkeley National Lab, Berkeley, Calif., 2011). Themajority of VSDs use the AC-DC-AC power conversion architecture; a DCpower distribution can eliminate the front-end AC-DC rectifier andthereby reduce power losses, cost, weight and volume of the convertersystem.

An emerging paradigm of operation and control of microgrids indistribution networks is the customer driven concept. Customers installutility compatible generation sources with an enhanced energy managementsystem (EMS) in the distribution grid. Their operation and control arethen dictated by community rules and individual preferences. The rapidaddition of new DER and types of microgrid and nanogrid loads make thepower grid design more complex, thereby making it more time-consumingand challenging to detect, preempt, and address problems in the grid. Asmall-scale renewable energy system presents a challenge as anintermittent power source leads to a mismatch between power productiontime and the power consumption of residential loads. Most residentialforced air HVAC systems in North America have varying runtimes becausethe system cycles on and off to meet conditioning demands. Conditioningruntimes are influenced by the temperature set on the thermostat thatalso allows the occupants to set the system in fan-only mode, to improvemixing, provide ventilation in systems equipped with an outdoor airintake, or maximize the amount of air that goes through the filter.Depending on the configuration of the system, the fan speed can varyunder different operation modes. The addition of DER to the gridinvolves not only electrical connection but also forecasting, controland coordination of variable power production and demand compared totraditional bulk generation and usage. The need exists for a renewableEMS that ensures the efficient use of locally produced power to matchthe demands of residential cooling loads with minimal impact, andmaintains the power quality of an onsite nanogrid and interconnectednanogrids of a cohesive direct current (DC) microgrid network.

SUMMARY

The following presents a simplified summary of some embodiments of thepresent disclosure to provide a basic understanding of the presentdisclosure. This summary is not an extensive overview of the presentdisclosure. It is not intended to identify key/critical elements of thepresent disclosure or to delineate the scope of the present disclosure.Its sole purpose is to present some embodiments of the presentdisclosure in a simplified form as a prelude to the more detaileddescription that is presented later.

An aspect of the present disclosure is an HVAC renewable energymanagement system (hereinafter “HVAC REMS”) comprising systems andmethods for optimal matching of local intermittent power production of ananogrid to the power consumption of an HVAC system. The HVAC REMScomprises one or more: central controller; intermittent distributedenergy resource (DER); source converter (e.g., DC-DC); DistributedStorage (DS) device; DS converter/controller; power bus; internal load(e.g., HVAC); sensing-communication line; and interface gateway to oneor more external grid for bi-directional power control, sharing, andconsumption. In various embodiments, the central controller is operablyconnected to control one or more said device, DER, source converter, DS,DS converter, power bus, internal load, and interface gateway via one ormore sensing and communication lines. In various embodiments, thecontrol method comprises the use of maximum power point tracking (MPPT)of one or more DER and measuring one or more cooling loads operatingwithin a nanogrid or a microgrid for power flow control to dynamicallymatch power production and consumption. In various embodiments, the oneor more internal load is connected to a Direct Current (DC) power busand powered by DC.

An aspect of the present disclosure is a HVAC REMS comprising an MPPTcontroller operably connected in series or parallel to one or more DER,one or more voltage converter, and at least one HVAC system, components,variable speed drive, compressor, motor, blower, fan, or cooling load.In various embodiments, the MPPT control method comprises the monitoringof one or more DER voltage and current output and modulates the dutycycle to the voltage converter to present the power requirement of saidcomponents of an HVAC system to said DER. In various embodiments, themethod comprises the modulation of the converter's pulse widthmodulation (PWM) duty cycle by tracking one or more DER' s maximum powerpoint generation. In various embodiments, the method comprises the useof one or more sensors (e.g., current, voltage, temperature) of at leastone DER to track maximum power point generation. In various embodiments,the method further comprises the use of one or more MPPT algorithms,including but not limited to, perturb and observe (P&O), incrementalconductance (IncCond), open-circuit voltage, short-circuit current,fuzzy logic (FL), or neural networks (NN) for stable, precise, and rapidtracking.

An aspect of the present disclosure is a HVAC REMS comprising a centralcontroller and one or more controllable node within a residentialstructure containing a nanogrid. In various embodiments, thecontrollable node comprises one or more voltage or current sensors tomonitor power consumption of an internal load. In various embodiments,the internal load is one or more standard household appliance, HVACsystem, components, variable speed drive, compressor, motor, or coolingload. In various embodiments, the controller controls the power supplyof one or more said load, preferably a thermostat-controlled HVAC systemor components, using one or more voltage converter. In variousembodiments, the controller controls in real time the power supply of anHVAC system via one or more sensors, including but not limited to,temperature, humidity, voltage, and current, to modulate the voltageapplied to the HVAC system. In various embodiments, the controllercomprises one or more microcontroller operably connected to one or moreDER, DS, capacitor, and switches, to communicate and control the HVACsystem operating within a nanogrid. In various embodiments, thecontroller enables a user to determine a chosen relative humidity (RH)set-point, airflow, temperature, or the like, of a conditioned space.

An aspect of the present disclosure is an HVAC REMS comprising powersharing, smart metering, communication between utilities and customers,two or more households, two or more nanogrids, and informationtechnologies for an advanced, secured, optimal control and protection ofa microgrid further comprising an internetwork of at least twonanogrids. In various embodiments, two or more nanogrid areinterconnected through one or more DC power bus line and disconnectedwith one or more DC breaker. In various embodiments, a nanogridcomprises a bipolar DC-link configuration, including but not limited to,between ground and 380 V. In various embodiments, at least two nanogridsare connected via one more communication network, including but notlimited to a wireless LAN, WAN, or cellular network, via networkcontrollers using at least one communication protocol, including but notlimited to TCP/IP. In various embodiments, two or more households cannegotiate, exchange, provide, receive or store power within a communityDS system, preferably a DS system comprising one or more battery,capacitor, supercapacitor, or the like, based on a microgrid rule orpolicy. In various embodiments, two or more households can negotiate,exchange, provide, or receive power from a utility or external powerdistributor, based on a microgrid rule or policy. In variousembodiments, two or more households can negotiate, exchange, provide, orreceive power from one another based on a microgrid rule or policy. Invarious embodiments, two or more nanogrids can communicate using saidHVAC REMS to coordinate power consumption.

An aspect of the present disclosure is an HVAC REMS comprising a systemand methods for the efficient use of DER power within a microgrid bymatching the power consumption of one or more HVAC system, components,variable speed drive, compressor, motor, blower, fan, or cooling loadoperating within at least two nanogrids and local DER production. Invarious embodiments, the method comprises the monitoring of one or moreMPPT tracking signals of one or more DER to determine poweravailability. In various embodiments, the method comprises one or moresaid MPPT algorithms to control the duty cycle of one or more convertersto alter voltage delivered to one or more HVAC loads. In variousembodiments, the method determines and adjusts the duty cycle of eachload in comparison to all loads within the microgrid based on set-point,temperature, humidity, and usage time. In various embodiments, themethod comprises providing power priority to the highest load. Invarious embodiments, the duty cycle is adjusted by a load priority ratioto the total available power of a microgrid. In various embodiments, thematched consumption hierarchical power system is coordinated through anHVAC REMS microgrid architecture.

An aspect of the present disclosure is an HVAC REMS architecturecomprising one or more physical exchange layer, converter controller,microgrid controller, gateway controller, home energy management system(HEM), communication network, cloud server, and cloud serverapplications. In various embodiments, the physical exchange layercomprises one or more bi-directional DC-DC converters. In variousembodiments, one or more nanogrid comprises a DC-DC controller forhandling communication with the physical layer DC-DC converter. Invarious embodiments, the cloud server applications include but are notlimited to one or more applications for storing data, measurements,visualization of power flow, debugging, maintenance, monitoring, dataanalysis, demand side management, power balance, power qualityassurance, system protection, system optimization, and security. Invarious embodiments, one or more remote client device can access cloudserver and application for management, seamless integration, andefficient operation of DC renewable generation, DC energy storagesystems, and DC smart cooling loads.

Specific embodiments of the present disclosure provide for a system forenergy management comprising an HVAC system comprising a compressor, amotor, a blower, and a variable speed drive, the HVAC system beingoperable to generate a cooling load; a distributed energy resourcecomprising a solar panel; a voltage converter operably engaged with thedistributed energy resource; a controller operably engaged with thedistributed energy resource, the voltage converter, and the HVAC system,the controller comprising a processor and a non-transitorycomputer-readable medium having instructions stored thereon to cause theprocessor to perform one or more actions, the one or more actionscomprising monitoring a voltage and current output of the distributedenergy resource; measuring power consumption of the cooling load of theHVAC system; modulating a duty cycle of the voltage converter; and,dynamically establishing a power flow between the distributed energyresource and the HVAC system according to the voltage and current outputand the power consumption of the cooling load.

Further specific embodiments of the present disclosure provide for amethod for energy management comprising monitoring, with a controlleroperably engaged with at least one current, voltage, or temperaturesensor, a voltage and current output of a distributed energy resource;measuring, with the controller operably engaged with at least onecurrent, voltage, or temperature sensor, a power consumption of aninternal energy load, the internal energy load comprising a cooling loadof an HVAC system; modulating, with the controller, a duty cycle of avoltage converter, the voltage converter being operably engaged with thedistributed energy resource and the HVAC system; establishing, with thecontroller being operably engaged with the voltage converter, a powerflow between the distributed energy resource and the HVAC systemaccording to the voltage and current output and the power consumption ofthe cooling load; and, establishing, with the controller being operablyengaged with the voltage converter, a power flow between the distributedenergy resource and a distributed energy storage device according to thevoltage and current output and the power consumption of the coolingload, the distributed energy storage device comprising a nanogrid.

Still further specific embodiments of the present disclosure provide fora method for renewable energy management comprising monitoring atracking signal of a distributed energy resource operating within amicrogrid, the microgrid comprising at least two nanogrids; measuring apower consumption of an internal energy load within the at least twonanogrids, the internal energy load comprising an energy load of an HVACsystem; modulating a duty cycle of a voltage converter according to theinternal energy load and a load priority parameter within the microgrid;and, establishing a power flow between the distributed energy resourceand the at least two nanogrids according to the internal energy load andthe load priority parameter.

The foregoing has outlined rather broadly the more pertinent andimportant features of the present disclosure so that the detaileddescription of the present disclosure that follows may be betterunderstood and so that the present contribution to the art can be morefully appreciated. Additional features of the present disclosure will bedescribed hereinafter which form the subject of the claims of thepresent disclosure. It should be appreciated by those skilled in the artthat the conception and the disclosed specific methods and structuresmay be readily utilized as a basis for modifying or designing otherstructures for carrying out the same purposes of the present disclosure.It should be realized by those skilled in the art that such equivalentstructures do not depart from the spirit and scope of the presentdisclosure as set forth in the appended claims.

BRIEF DESCRIPTION OF DRAWINGS

The above and other objects, features and advantages of the presentdisclosure will be more apparent from the following detailed descriptiontaken in conjunction with the accompanying drawings, in which:

FIG. 1 is an illustration of an HVAC renewable energy managementplatform, according to an embodiment of the present disclosure;

FIG. 2 is an illustration of an MPPT controller architecture foroperating an HVAC load, according to an embodiment of the presentdisclosure;

FIG. 3 is a logic flow diagram illustrating a process algorithm forimplementation by an MPPT controller, according to an embodiment of thepresent disclosure;

FIG. 4 is a diagram of a nanogrid control architecture of the HVACrenewable energy management platform, according to an embodiment of thepresent disclosure;

FIG. 5 is an illustration of an MPPT controller architecture forproviding constant voltage to a DC bus of a nanogrid, according to anembodiment of the present disclosure;

FIG. 6 is a block diagram of an electrical node system controlarchitecture for a nanogrid supporting the operation of a HVAC system,according to an embodiment of the present disclosure;

FIG. 7 is a logic flow diagram illustrating a process for powermanagement of an HVAC load within a nanogrid, according to an embodimentof the present disclosure;

FIG. 8 is a logic flow diagram illustrating a process for power capacitymanagement of a distributed storage source supporting an HVAC systemwithin a nanogrid, according to an embodiment of the present disclosure;

FIG. 9 is a logic flow diagram illustrating a process for controlling anHVAC system within a nanogrid, according to an embodiment of the presentdisclosure;

FIG. 10 is a block diagram of a microgrid architecture supporting theoperation of a HVAC renewable energy management system, according to anembodiment of the present disclosure; and

FIG. 11 is a diagram of an HVAC REMS network communication architecture,according to an embodiment of the present disclosure.

DETAILED DESCRIPTION

Exemplary embodiments are described herein to provide a detaileddescription of the present disclosure. Variations of these embodimentswill be apparent to those of skill in the art. Moreover, certainterminology is used in the following description for convenience onlyand is not limiting. For example, the words “right,” “left,” “top,”“bottom,” “upper,” “lower,” “inner” and “outer” designate directions inthe drawings to which reference is made. The word “a” is defined to mean“at least one.” The terminology includes the words above specificallymentioned, derivatives thereof, and words of similar import Likereference numbers refer to like elements throughout.

As used herein the term “HVAC” includes systems providing both heatingand cooling, heating only, cooling only, as well as systems that provideother occupant comfort and/or conditioning functionality such ashumidification, dehumidification, and ventilation.

As used herein the term “residential” when referring to an HVAC systemmeans a type of HVAC system that is suitable to heat, cool and/orotherwise condition the interior of a building that is primarily used asa single-family, a duplex, apartment, office, retail structure ordwelling.

Without loss of generality, some descriptions further herein below willrefer to an exemplary scenario in which the innovation is used in a homeor housing environment. However, it is to be appreciated that thedescribed embodiments are not so limited and are applicable to use ofsuch innovation in multiple types and locations of HVAC systems.

A small-scale renewable energy system presents a challenge as anintermittent power source leads to a mismatch between power productiontime and the power consumption of residential loads such as an HVACsystem. Embodiments of the present disclosure enable an HVAC renewableenergy management system (herein after “HVAC REMS”) and components thatensure the efficient use of locally produced power from an onsitenanogrid and interconnected nanogrids of a cohesive direct current (DC)microgrid network. The HVAC REMS comprises a central controller forcontrolling one or more intermittent Distributed Energy Resource (DER),source converter (e.g., DC-DC), Distributed Storage (DS) device, DSconverter, power bus, internal load (e.g., DC-based HVAC), and interfacegateway to one or more external grid for bi-directional power control,sharing, and consumption. The HVAC REMS and various system hardware andsoftware elements are configured for internetworking communication(e.g., Internet, cloud services, etc.), management, control, demand sidemanagement, power balance, using maximum power point tracking (MPPT) toshift power consumption, dynamic matching of local DER production, powerquality assurance, system protection, power interconnection management,interface management, metering, revenue settlement, system optimization,and security. The system can match local power production with anindividual household's power consumption to reduce intermittency andultimately total microgrid consumption.

Referring to FIG. 1, an illustration 100 of an HVAC renewable energymanagement platform is shown, according to various embodiments. The HVACREMS comprises a central controller 102, one or more intermittentdistributed energy resource (DER) 104, 106, source converter 108, DSconverter/controller 110, Distributed Storage (DS) device 112, power bus114, one or more internal loads (e.g., HVAC) 116, 118, one or moresensing communication line 120, and interface gateway 122 to one or moreexternal grid for bi-directional power control, sharing, andconsumption. In various embodiments, DER 104 comprises one or more windturbine, preferably a small-scale wind turbine, having a non-limitingrated capacity (e.g., 300-1000 W), and capable of providing one or morevoltage output (e.g., 12, 24, 48V, etc.). In various embodiments, DER106 comprises one or more photovoltaic module, having a non-limitingrated capacity (e.g., 200-500 W), and capable of providing one or morevoltage output (e.g., 30 to 40 V). In various embodiments, sourceconverter 108 comprises a DC-DC converter capable of converting one ormore source voltages from at least one said DER to a DV bus voltagelevel of 380 V. In various embodiments, DS device 112 comprises one ormore energy storage device, including but not limited to a battery, acapacitor, a supercapacitor, a fly-wheel, a battery of an electricvehicle, or combinations thereof. In various embodiments, DSconverter/controller 110 comprises a bi-directional controller, capableof sensing one or more voltage level of a DS, and controlling thecharging or discharging of said DS. In various embodiments, power bus114 comprises a DC power bus, preferably a power bus operating at avoltage, including but not limited to, a voltage level of 380 V. Invarious embodiments, one or more internal loads are connected to powerbus 114, and powered at one or more voltage level, including but notlimited to, 12 V, 24 V, or 48 V via one or more load converter designedfor said various voltage level. In various embodiments, the one or moreinternal load comprises an HVAC system, further comprising one or moreinternal loads, optionally operating under variable frequency drive(VSD), including but not limited to a compressor, fan, and a blower. Invarious embodiments, gateway 122 comprises a bi-directional converter(e.g. DC-AC) for interfacing with one or more external grid, including ananogrid, a microgrid, or a national grid. In various embodiments, thecentral controller is operably connected to control one or more saiddevice, DER, source converter, DS, DS converter, power bus, internalload, and interface gateway via one or more sensing and communicationline 120. In various embodiments, the control method comprises the useof maximum power point tracking (MPPT) of one or more DER 104, 106 andmeasuring one or more cooling loads 118 operating within a nanogrid or amicrogrid for power flow control to dynamically match power productionand consumption.

Referring to FIG. 2, an illustration 200 of an MPPT controllerarchitecture for operating an HVAC load is shown, according to variousembodiments. The MPPT controller architecture comprises an MPPTcontroller 202 operably connected in series or parallel to one or moreDER 204, one or more voltage converter, preferably an interleavedconverter 206, and at least one HVAC system, components, variable speeddrive, compressor, motor 208, blower, fan, or cooling load. In variousembodiments, the MPPT controller 202 monitors (shown as dottedconnections) one or more DER voltage 210 and current output 212 andmodulates the duty cycle signals 214 to the interleaved converter 206 topresent the power requirement of said components, motor 208, of an HVACsystem to said DER. In various embodiments, the method comprises themodulation of the converter's pulse width modulation (PWM) duty cycle,via one or more PWM signals 216 by tracking one or more DER' s maximumpower point generation, generating one or more said signals via a motorcontroller 218. The PMW signals 216 are generated and sent to aninverter 220, converting DC power from the interleaved converter to ACfor actuating motor 208 in conjunction with one or more Hall sensor 222,one or more voltage signal 224 and current signal 226. In variousembodiments, MPPT controller 202 modulates the PWM signals 216 bysensing one or more voltage signal 228 and current signal 230 ofinterleaved converter 206. In various embodiments, the architecturecomprises one or more motor 208, including but not limited to aninductance motor, AC motor, commutated motor, DC motor, BLDC motor,magnetic motor, PMDC motor, or the like. Depending on the type of AC orDC powered motor 208 chosen, the MPPT and motor controllers may operatewith or without inverter 220. In various embodiments, the architecturecomprises a motor 208 configured to operate under variable frequencycontrol (VFD), as a variable speed drive (VSD). In various embodiment,the VFD or VSD comprises one or more speed control methods, includingbut not limited to scalar, vector, direct torque control, the like, orcombinations thereof. In various embodiments, motor 208 or the like isincorporated into one or more HVAC system or components, including butnot limited to air handling unit, cooling tower fan, cooling tower pump,circulating pump, compressor, fan, blower, damper, or the like. Invarious embodiments, the MPPT controller 202 comprises the use of one ormore sensor 232 (e.g., current, voltage, temperature) of at least oneDER 204 to track maximum power point generation. In various embodiments,motor controller 218 comprises a speed controller and a limiter. Invarious embodiments, the PWM signals are fed into one or more powerdriver, incorporating one or more Insulated Gate Bipolar Transistors(IGBT) within inverter 220 for actuating motor 208. In variousembodiments, the MPPT controller 202 executes one or more algorithm,including but not limited to, constant voltage control (CVC), perturband observe (P&O), hill climbing (H&C), incremental conductance(IncCond), open-circuit voltage, short-circuit current, fuzzy logic(FL), or neural networks (NN) for stable, precise, and rapid tracking.

FIG. 3 is a logic flow diagram 300 illustrating a process algorithm forimplementation by an MPPT controller, according to various embodiments.The MPPT algorithm is based on the premise that for any environmentalcondition, for example, the specific solar irradiance/ambienttemperature affecting a PV module 106, there exists one operating pointfor maximum power extraction. In various embodiments, the MPPTcontroller algorithm comprises the monitoring of one or more PV outputvoltage and current (e.g., 210, 212) and alters the duty cycle (e.g.,214) to the DC-DC converter (e.g., 206) to present the PV system withrequired impedance. The DC-DC converter forces the PV module to operateat its maximum power point (MPP) by presenting a variable load to thePV. In a preferred embodiment, the incremental conductance (IncCond) ischosen due to its high yield, producing more energy, under vastlychanging conditions and its lower oscillations. IncCond is based on theobservation of the P-V characteristic curve. The MMP can be calculatedusing the relation between dI/dV and −I/V. If dP/dV is negative thenMPPT lies on the right side of a recent position, and if the MPP ispositive, then the MPPT is on the left side. The MPP is reached whendP/PV. If dP/dV is negative or positive, the duty cycle needs to bealtered to ensure the value is returned to zero. The algorithm comprisesa starting step (302) that proceeds to measure V & I (step 304) of aDER, preferable a PV, and a calculation of dI and dV (step 306).Decision point is made at step 308 on whether dV is equal to zero (0) ornot. If dV is equal to zero, then the algorithm proceeds to determine(step 310) whether dI is equal to zero or not. If dI is equal to zerothen the duty cycle of the converter is increased (step 312). Thealgorithm then repeats starting at step 302 (labeled as Return).Continuing with the alternative at step 308, if dV does not equal zero,then dI/V is determined (step 314) to be equal or not equal to I/V. IfdI/dV is equal, then the duty cycle is increased at step 316 and thealgorithm then repeats starting at step 302 (labeled as Return). IfdI/dV is not equal to I/V at step 314, the dI/dV is determined (step318) whether it is greater than −I/V. If it is NO, then the duty cycleis decreased at step 320 and the algorithm then repeats starting at step302 (labeled as Return). If YES at 318, then dV is determined (step 322)to be greater or not than zero. If YES, the duty cycle is increased atstep 324 and the algorithm then repeats starting at step 302 (labeled asReturn). If NO at step 322, then the duty cycle is decreased at step 326and the algorithm then repeats starting at step 302 (labeled as Return).Continuing with the alternative step at 310, if dI is not equal to zero,then a determination is made whether it is greater or not than zero(step 328). If it is NO, then the duty cycle is decreased at step 330and the algorithm then repeats starting at step 302 (labeled as Return).If YES, then the duty cycle is increased at step 332 and the algorithmthen repeats starting at step 302 (labeled as Return). In variousembodiments, the said IncCond algorithm can be implemented using one ormore IC on a microcontroller, microprocessor, the like, or combinationsthereof.

Referring to FIG. 4, a diagram 400 of a nanogrid control architecture ofthe HVAC REMS is shown, according to various embodiments. The HVAC REMScomprises a central controller 402 and one or more controllableelectrical node 404 within a residential structure containing ananogrid. The nanogrid comprises a DER 406, implementing an MPPTcontroller 408, and power conversion with voltage controller 410,providing a voltage source for one or more internal power source node404, via a DC bus 412. The nanogrid further comprises a DS 414 for powerstorage connected to said DC bus 412 to provide backup power to at leastone electrical node 404. In various embodiments, the controller 402comprises one or more control connection 416 (dotted line) for controlcommunication to the DER 406, MPPT controller 408, voltage converter410, bus line 412, DS 414, gateway converter 418, and gateway interface420. In various embodiments, the one or more said nanogrid componentsare powered by the DC power bus 412. In various embodiments, acontrollable node 404 comprises one or more voltage or current sensor422 to monitor power consumption of an internal load 424. In variousembodiments, the internal load is one or more standard householdappliance. In various embodiments, the internal load comprises a HVACsystem 426, components, variable speed drive, compressor, motor, orcooling load. In various embodiments, the controller 402 controls thepower supply of one or more said load, using one more voltage converter410, preferably a constant voltage controller. In various embodiments,the controller 402 controls in real time the power supply of an HVACsystem via one or more sensors 422, including but not limited totemperature, humidity, voltage, and current, to modulate the voltageapplied to the HVAC system 426. In various embodiments, sensors 422 mayoperate in conjunction with a thermostat 428 or as a component of athermostat. In various embodiments, the controller comprises one or moremicrocontroller, operably connected to one or more DER, DS, capacitor,switches, to communicate and control the HVAC system operating within ananogrid. In various embodiments, the controller enables a user todetermine a chosen relative humidity (RH) set-point, airflow,temperature, or the like, of a conditioned space.

Referring to FIG. 5, an illustration 500 of an MPPT controllerarchitecture for providing constant voltage to a DC bus of a nanogrid isshown, according to various embodiments. The MPPT controllerarchitecture comprises an MPPT controller 502 operably connected to, inseries or parallel to, one or more DER 504, one or more voltageconverter, preferably an interleaved converter 506, at least one voltageconverter 508, and a power bus 510, providing power to one or more saidelectronically controllable nodes of FIG. 4. In various embodiments, theMPPT controller 502 monitors (shown as dotted connections) one or moreDER voltage 510 and current output 512 and modulates the duty cyclesignals 514 to the interleaved converter 506 to present the powerrequirement of bus 516. In various embodiments, the method comprises themodulation of the converter's pulse width modulation (PWM) duty cycle,via one or more PWM signals 518 by tracking one or more DER' s maximumpower point generation, generating one or more said signals to voltageconverter 508. The PMW signals 518 are generated and sent to converter508, converting DC power from the interleaved converter to one or morevoltage level for power bus 510. In various embodiments, MPPT controller502 modulates the PWM signals 518 by sensing one or more voltage signal520 and current signal 522 of interleaved converter 506. In variousembodiments, voltage converter 508 is preferably one or more, but notlimited to, a buck converter, a synchronous buck converter, enabling thesystem to output a constant voltage (380V) to DC bus 516. In variousembodiments, the voltage converter comprises, including but not limitedto, one or more control FET, gate driver, PWM generator, synchronizingFET, inductor, capacitor, compensation network, amplifier, erroramplifier, or combinations thereof. In various embodiments, thevoltage-mode control and voltage-mode error amplifier can be stabilizedusing one or more PI or PID type compensator, depending on the chosenelectrolytic capacitor, tantalum capacitor, or high-performance POS-cap,SP-Cap output capacitors. In an alternative embodiment, voltageconverter 508 comprises a digitally controlled DC-DC buck converterperformed by field-programmable gate array (FPGA) circuitry. The voltageand current-mode control are based on a voltage control oscillator (VCO)performed measurements regarding output-voltage and inductor currentdigital-counters to obtain integral values for the output voltage andinductor current. In various embodiments, one or more instantaneousinductor current-value-measurement is used for the switching action.When the VCO is used for the inductor current measurement, the integralis measured during the switching-on time set as an observation intervaland the switching action occurs based on this measurement. In variousembodiments, this principle enables full digitalization of the voltage-and current-control loop and also the used measurement principle iscapable of rejecting the switching disturbances during current andvoltage measurements. In various embodiments, all the tasks for thecurrent and voltage control is implemented within FPGA amplifiers, avoltage-mode control, and a voltage error amplifier.

Referring to FIG. 6, a block diagram 600 of an electrical node systemcontrol architecture for a nanogrid supporting the operation of a HVACsystem is shown, according to various embodiments. The system controlarchitecture comprises a central controller 602 and multiple controlnode 604 providing power to one or more DC load 608, 610 of the presentdisclosure. In various embodiments, one or more node 604 are capable ofcurrent and voltage sensing applied to load 608, 610. In variousembodiments, the controller 602 controls one or more components of thearchitecture through one or more communication channel 612 (shown asdotted lines). In various embodiments, the system control architecturecomprises one or more switch 614 connecting one or more node 604 to DCbus 616. In various embodiments, the system control architecturecomprises one or more backup energy storage device 618 connected to oneor more switch 614 or DC bus 616 via a DS controller 620. In variousembodiments, one or more switch 614 is controlled by one or moremicrocontroller 622 and monitors one or more current and voltage ofstorage device 618 and one or more node 604 sensor outputs. For example,microcontroller 622 monitors the voltage level of storage device 618. Ifthe voltage level drops below a specified level, due to leakage currentor load activity, a charge switch 614 is activated to restore voltage toan adequate level. In various embodiments, the microcontroller executesone or more algorithms using these outputs for control decision-making.In various embodiments, the microcontroller sends and receivesinformation to/from the central controller 602 relaying one or more load608, 610 status and implementing control for power management.

FIG. 7 is a logic flow diagram 700 illustrating a process for powermanagement of an HVAC load within a nanogrid, according to variousembodiments. The process is based on the premise that for any nanogridload condition the HVAC load has priority over a non-HVAC load. Theprocess comprises a starting step (702) that proceeds to determine (step704) that a non-HVAC load 608 has been turned on. An electric node 604then requests (step 706) power. The central controller 602 then requests(step 708) the status of the MPPT controller 502 for the availablecapacity of one or more DER 504. The MPPT controller replies (step 710).The central controller 602 then relays (step 712) the available capacityto the requesting node. The node of the HVAC system monitors (step 714)its power requirement. If there is sufficient capacity, then the centralcontroller 602 distributes (step 716) to the node powering a non-HVACload. In a final step, the central controller 602 switches (step 718)one or more relay switch 614 to distribute power to a node 604 of anon-HVAC load.

FIG. 8 is a logic flow diagram 800 illustrating a process for powercapacity management of a distributed storage source (e.g., device 618)supporting an HVAC system within a nanogrid, according to variousembodiments. The premise of the process is to measure a DS' s State ofCharge (SoC) to monitor the operation of a battery when it's charging ordischarging. In a preferred embodiment, the control of device 618comprises one or more limit protection methods using one or more valueor range of SoC. In various embodiments, the energy storage systemreceives one or more power command from central controller 602 formanaging one or more fluctuation of an output of one or more DER,preferably a PV module. In various embodiments, the sum of thedifference between a Power (load) and Power (PV) and one or more commandPower (EMS-schedule) are sent as input into device 618 via controller620. In various embodiments, frequency division is conducted on the sumin order to retrieve its low frequency components. In variousembodiments, the low frequency component of a Power (battery-ref) willbe managed by the storage device 618 to prevent frequent batterycharging/discharging. In various embodiments, a reference output currentof the battery (i.e., Current (I) battery-ref) is derived from the Power(battery_ref). In various embodiments, the charging or discharging ofdevice 618 can be determined by measuring the real-time SoC of device618. The process comprises a starting step (802) that proceeds tomonitor (step 804) I battery-ref. At step 806, a decision is madewhether Soc is between 0.1 and 0.9 or not. When SoC is between the saidlimits, the device 618 can work at charging/discharging mode normally. Alimiting protection is required to avoid the batterycharging/discharging. The limited range is set (step 808) as −Ibattery_ref_max≤I battery_ref≤I battery_ref_max where I battery_ref_maxis the upper limit and −I battery_ref_max is the lower limit. Device 618is discharging when I battery_ref≥0 and s charging I battery_ref≤0. Atstep 810, if SOC≥0.9, then the SoC value of device 618 exceeds the safeoperation range. Device 618 is only permitted to work in dischargingmode. A limiting protection is required (step 812) to implement andcomprise the range set as 0≤I battery_ref≤I battery_ref_max. When SoC is0.1, then the SoC value of device 618 operating (step 814) below thesafe operation range. Device 618 is only permitted to work at chargingmode. A limiting protection is required to avoid the battery device fromdischarging and the range is set as −Ibattery_ref_max≤Ibatter_ref ≤0.

FIG. 9 is a logic flow diagram 900 illustrating a process forcontrolling an HVAC system within a nanogrid, according to variousembodiments. The premise of the process is the control of the frequencyof on/off cycles of the HVAC system depending on the availability of PVpower and reducing the frequency of “on” time while PV power isoff-line. In various embodiments, controller 602 controls one or morenode 604, supplying at least one HVAC system or component, byestablishing one or more set-point (e.g. temperature threshold) lowertemperature thresholds and limits received, for example from athermostat, and powering the HVAC unit to its lower limit when PV poweris available and allowing the temperature to vary between a lowerthreshold and one or more limit. When insufficient PV power is present,the temperature of a conditioned space can be increased to an upperlimit and allow oscillation between its upper threshold and limit. Theprocess comprises a starting step (902) that proceeds to determine (step904) whether the MPPT signal is greater than or equal to the powerrequired for operating an HVAC system. If it is YES, then one or moreset-point (SP) (e.g., temperature), is determined (step 906) whether tobe equal to or less than a specified Lower Limit. If YES, then the SP isdetermined (step 908) whether to be equal to or greater than a LowerThreshold (TH). If YES, then the process repeats starting at step 902(labeled as Return). If NO, then the Power out is set (step 910) tozero. At step 906, a power out is set (step 912) to 1 (full) if a NOdecision is made. At step 904, a NO decision proceeds to step 914 whereanother determination is made whether the SP is equal to or greater thanan Upper Limit. If NO, then a power out is set (step 916) equal to 0. IfYES, then another determination is made (step 918) of whether the SP isequal or greater than an Upper TH. If YES, then a power out is set (step920) to Full (1). If NO, then the process repeats starting at step 902(labeled as Return).

FIG. 10 is a block diagram 1000 of a microgrid architecture supportingthe operation of a HVAC REMS, according to various embodiments. The HVACREMS comprises multiple individual nanogrids located with one or moreresidential structure 1002 (shown with identical elements forillustration purposes). Each residential structure comprises a nanogridfurther comprising at least one nanogrid controller 1004, DER 1006, DS1008, internal load 1010 (e.g., DC HVAC system), smart meter 1012, andgateway 1014. In various embodiments, two or more nanogrids of two ormore residential structure 1002 enable power sharing, smart metering,communication between utilities and customers, and two or morehouseholds. In various embodiments, two or more nanogrids compriseinformation technologies for an advanced, secured, optimal control andprotection of a microgrid 1016. In various embodiments, the two or morenanogrids are interconnected through one or more DC power bus line 1018and disconnected with one or more DC breaker. In various embodiments, ananogrid within residential structure 1002 comprises a bipolar DC-linkconfiguration, including but not limited to, between ground and 380 V.In various embodiments, at least two nanogrids are connected via onemore communication network, including but not limited to a wireless LAN,WAN, cellular network, via network controllers using at least onecommunication protocol, including but not limited to TCP/IP. In variousembodiments, two or more households can negotiate, exchange, provide,receive or store power within a community DS system 1020, preferably aDS system comprising one or more battery, capacitor, supercapacitor, orthe like, based on a microgrid rule or policy. In various embodiments,two or more households can negotiate, exchange, provide, or receivepower from a utility or external power distributor, based on a microgridrule or policy, via one or more grid 1022. In various embodiments, twoor more households can negotiate, exchange, provide, or receive powerfrom one another based on a microgrid rule or policy. In variousembodiments, two or more nanogrids can communicate using said HVAC REMSto coordinate power consumption. In various embodiments, the method ofcoordinating power consumption comprises the monitoring of one or moreMPPT tracking signals of one or more DER 1006 to determine poweravailability. In various embodiments, the method comprises one or moresaid MPPT algorithms to control the duty cycle of one or more convertersto alter voltage delivered to one or more HVAC loads 1010. In variousembodiments, the method determines and adjusts the duty cycle of eachload in comparison to all loads within the microgrid based on set-point,temperature, humidity, and usage time. In various embodiments, themethod comprises providing power priority to the highest load. Invarious embodiments, the duty cycle is adjusted by a load priority ratioto the total available power of a microgrid. In various embodiments, thematched consumption hierarchical power system is coordinated throughsaid HVAC REMS microgrid architecture.

Referring to FIG. 11 a diagram 1100 of an HVAC REMS networkcommunication architecture is shown, according to various embodiments.The network communication architecture within a residential structure1102 comprises one or more physical exchange layer 1104, convertercontroller 1106, microgrid controller 1108, gateway controller 1110,home energy management system (HEM) 1112, communication network 1114(e.g., Internet), cloud server 1116, cloud server applications 1118, andone or more database 1120. In various embodiments, the physical exchangelayer 1104 comprises one or more bi-directional DD-DC converters.Communication network 1114 may comprise any one and/or the combinationof the following: a direct interconnection; a Local Area Network (LAN);a wide area network (WAN); a Metropolitan Area Network (MAN); publicnetwork; the Internet; a wireless network (e.g., Bluetooth, Wi-Fi,cellular, 2G, 3G, 4G, 5G, LITE, etc.); and or the like. It is understoodthat any suitable network interface, network, network communicationprotocol, and network communication standards may be used withoutdeparting from the scope of the present teachings. In variousembodiments, one or more nanogrid within residential structure 1102comprises a DC-DC controller 1106 for handling communication with thephysical layer 1104 DC-DC converter. In various embodiments, the cloudserver applications 1118, including but not limited to one or moreapplications 1122 for storing data, measurements, visualization of powerflow, debugging, maintenance, monitoring, data analysis, demand sidemanagement, power balance, power quality assurance, system protection,system optimization, and security. In various embodiments, one or moreremote client device 1112, 1124 can provide access to cloud server 1116and one or more applications 1118 for management, seamless integration,and efficient operation of DC renewable generation, DC energy storagesystems, and DC smart cooling loads.

The above detailed description includes references to the accompanyingdrawings, which form a part of the detailed description. The drawingsshow, by way of illustration, specific embodiments in which the presentdisclosure may be practiced. These embodiments are also referred toherein as “examples.” Such examples may include elements in addition tothose shown or described. However, the present inventors alsocontemplate examples in which only those elements shown or described areprovided. Moreover, the present inventors also contemplate examplesusing any combination or permutation of those elements shown ordescribed (or one or more aspects thereof), either with respect to aparticular example (or one or more aspects thereof), or with respect toother examples (or one or more aspects thereof) shown or describedherein.

In this document, the terms “a” or “an” are used, as is common in patentdocuments, to include one or more than one, independent of any otherinstances or usages of “at least one” or “one or more.” In thisdocument, the term “or” is used to refer to a nonexclusive or, such that“A or B” includes “A but not B,” “B but not A,” and “A and B,” unlessotherwise indicated. In this document, the terms “including” and “inwhich” are used as the plain-English equivalents of the respective terms“comprising” and “wherein.” Also, in the following claims, the terms“including” and “comprising” are open-ended, that is, a system, device,article, or process that includes elements in addition to those listedafter such a term in a claim are still deemed to fall within the scopeof that claim. Moreover, in the following claims, the terms “first,”“second,” and “third,” etc. are used merely as labels, and are notintended to impose numerical requirements on their objects.

Method examples described herein may be machine or computer-implementedat least in part. Some examples may include a computer-readable mediumor machine-readable medium encoded with instructions operable toconfigure an electronic device to perform methods as described in theabove examples. An implementation of such methods may include code, suchas microcode, assembly language code, a higher-level language code, orthe like. Such code may include computer readable instructions forperforming various methods. The code may form portions of computerprogram products. Further, in an example, the code may be tangiblystored on one or more volatile, non-transitory, or non-volatile tangiblecomputer-readable media, such as during execution or at other times.Examples of these tangible computer-readable media may include, but arenot limited to, hard disks, removable magnetic disks, removable opticaldisks, memory cards or sticks, random access memories (RAMs), read onlymemories (ROMs), and the like.

The above description is intended to be illustrative, and notrestrictive. For example, the above-described examples (or one or moreaspects thereof) may be used in combination with each other. Otherembodiments may be used, such as by one of ordinary skill in the artupon reviewing the above description.

The Abstract is provided to comply with 37 C.F.R. § 1.72(b), to allowthe reader to quickly ascertain the nature of the technical disclosure.It is submitted with the understanding that it will not be used tointerpret or limit the scope or meaning of the claims. Also, in theabove Detailed Description, various features may be grouped together tostreamline the disclosure. This should not be interpreted as intendingthat an unclaimed disclosed feature is essential to any claim. Rather,inventive subject matter may lie in less than all features of aparticular disclosed embodiment.

Thus, the following claims are hereby incorporated into the DetailedDescription, with each claim standing on its own as a separateembodiment, and it is contemplated that such embodiments may be combinedwith each other in various combinations or permutations. The scope ofthe present disclosure should be determined with reference to theappended claims, along with the full scope of equivalents to which suchclaims are entitled.

What is claimed is:
 1. A system for renewable energy managementcomprising: an HVAC system comprising a compressor, a motor, a blower,and a variable speed drive, the HVAC system being operable to generate acooling load; a distributed energy resource comprising a solar panel; avoltage converter operably engaged with the distributed energy resourceand the HVAC system; a controller operably engaged with the distributedenergy resource, the voltage converter, and the HVAC system, thecontroller comprising a processor and a non-transitory computer-readablemedium having instructions stored thereon to cause the processor toperform one or more actions, the one or more actions comprising:monitoring a voltage and current output of the distributed energyresource; measuring power consumption of the cooling load of the HVACsystem; modulating a duty cycle of the voltage converter; and,establishing a power flow between the distributed energy resource andthe HVAC system according to the voltage and current output and thepower consumption of the cooling load.
 2. The system of claim 1 furthercomprising a distributed energy storage device comprising a nanogrid,the distributed energy storage device being operably engaged with thedistributed energy resource, the voltage converter, and the HVAC system.3. The system of claim 2 further comprising at least one current,voltage, or temperature sensor operably engaged with the distributedenergy resource and the controller.
 4. The system of claim 3 wherein thecontroller is configured to track a maximum power point generation ofthe distributed energy resource in response to an input by the at leastone current, voltage, or temperature sensor.
 5. The system of claim 3wherein the at least one current, voltage, or temperature sensorcomprises at least one controllable node within the nanogrid.
 6. Thesystem of claim 2 further comprising an external distributed energystorage device comprising a microgrid being operably engaged with thedistributed energy storage device comprising the nanogrid.
 7. The systemof claim 6 wherein the one or more actions of the processor furthercomprise establishing a power flow between the distributed energystorage device and the HVAC system according to the voltage and currentoutput of the distributed energy resource and the power consumption ofthe cooling load.
 8. The system of claim 6 wherein the one or moreactions of the processor further comprise establishing a power flowbetween the distributed energy resource and the distributed energystorage device according to the voltage and current output of thedistributed energy resource and the power consumption of the coolingload.
 9. The system of claim 6 wherein the one or more actions of theprocessor further comprise establishing a power flow between thedistributed energy storage device and the external distributed energystorage device according to the voltage and current output of thedistributed energy resource and the power consumption of the coolingload.
 10. A method for renewable energy management comprising:monitoring, with a controller operably engaged with at least onecurrent, voltage, or temperature sensor, a voltage and current output ofa distributed energy resource, the distributed energy resourcecomprising a solar panel; measuring, with the controller operablyengaged with the at least one current, voltage, or temperature sensor, apower consumption of an internal energy load, the internal energy loadcomprising a cooling load of an HVAC system; modulating, with thecontroller, a duty cycle of a voltage converter, the voltage converterbeing operably engaged with the distributed energy resource and the HVACsystem; establishing, with the controller being operably engaged withthe voltage converter, a power flow between the distributed energyresource and the HVAC system according to the voltage and current outputand the power consumption of the cooling load; and, establishing, withthe controller being operably engaged with the voltage converter, apower flow between the distributed energy resource and a distributedenergy storage device according to the voltage and current output andthe power consumption of the cooling load, the distributed energystorage device comprising a nanogrid.
 11. The method of claim 10 furthercomprising establishing, with the controller being operably engaged witha distributed energy storage converter, a power flow between thedistributed energy storage device and the HVAC system according to thevoltage and current output of the distributed energy resource and thepower consumption of the cooling load.
 12. The method of claim 10further comprising calculating, with the controller operably engagedwith the at least one current, voltage, or temperature sensor, a maximumpower point generation parameter of the distributed energy resource. 13.The method of claim 10 further comprising establishing, with thecontroller operably engaged with a power interface gateway, a power flowbetween the distributed energy storage device and an externaldistributed energy storage device, the external distributed energystorage device comprising a microgrid.
 14. The method of claim 10further comprising modulating one or more components of the HVAC systemin response to the voltage and current output of the distributed energyresource.
 15. A method for renewable energy management comprising:monitoring a tracking signal of a distributed energy resource operatingwithin a microgrid, the microgrid comprising at least two nanogrids anda distributed energy storage system; measuring a power consumption of aninternal energy load within the at least two nanogrids, the internalenergy load comprising an energy load of one or more electricalappliance; modulating a duty cycle of a voltage converter according tothe internal energy load and a load priority parameter within themicrogrid; and, establishing a power flow between the distributed energyresource and the at least two nanogrids according to the internal energyload and the load priority parameter.
 16. The system of claim 15 furthercomprising establishing a power flow between the distributed energyresource and the distributed energy storage system according to theinternal energy load and the load priority parameter.
 17. The system ofclaim 15 wherein the one or more electrical appliance is an HVAC system.18. The system of claim 17 further comprising modulating one or morecomponents of the HVAC system in response to a voltage and currentoutput of the distributed energy resource.
 19. The system of claim 15establishing a power flow between the distributed energy storage systemand the at least two nanogrids according to the internal energy load andthe load priority parameter.
 20. The system of claim 15 furthercomprising modulating the energy load of the one or more electricalappliance according to a total available power parameter of themicrogrid.